flywheel

Parse JSONL session logs to compute per-skill health metrics and identify refinement patterns.

Updated Mar 14, 2026
One-click install
npx skills add https://github.com/BertCalm/xo-ox-claude-config --skill flywheel-bertcalm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: flywheel
Source: https://github.com/BertCalm/xo-ox-claude-config/tree/main/skills/flywheel
Command: npx skills add https://github.com/BertCalm/xo-ox-claude-config --skill flywheel-bertcalm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automatically analyzes how other skills are used and identifies areas for improvement, ensuring the entire skill ecosystem continuously gets better.

Core Features & Use Cases

  • Automated Skill Analysis: Monitors usage patterns, correction rates, and user sentiment for all skills.
  • Proactive Refinement: Identifies skills that need updates, description optimization, or are underutilized.
  • Use Case: When a skill is frequently corrected by users, the Flywheel flags it for review and suggests specific changes to its underlying logic or instructions.

Quick Start

Invoke the flywheel skill to analyze skill usage and suggest improvements.

Frequently Asked Questions about flywheel

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze skill usage data to identify areas for improvement?

Skill usage data is analyzed by parsing JSONL session logs to compute per-skill health metrics, monitoring usage patterns, correction rates, and user sentiment to identify actionable patterns for enhancement.

What is skill refinement and how does automated analysis trigger improvement cycles?

Skill refinement is the process of continuously monitoring invocation data to trigger improvement cycles. Automated analysis flags frequently corrected skills for review and suggests specific changes to underlying logic or instructions.

How do I optimize underutilized skills in an AI ecosystem?

To optimize underutilized skills in an AI ecosystem, you monitor usage patterns and proactively identify skills needing description optimization or updates, ensuring the entire ecosystem continuously gets better.

Can I compute ecosystem health metrics from JSONL session logs?

Yes, you can compute ecosystem health metrics by parsing a JSONL session log. This process calculates per-skill health metrics and identifies actionable patterns to maintain and optimize overall performance and user satisfaction.

Do I need any external dependencies to run automated skill performance analysis?

No external dependencies are required to run automated skill performance analysis. The ecosystem health monitoring operates independently using internal scripts and references to parse logs and suggest improvements.

Why does automated skill analysis flag certain skills for review and update?

Automated skill analysis flags skills for review when it detects frequent user corrections or underutilization, proactively suggesting specific changes to underlying logic, instructions, or descriptions to improve performance.